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Detecting acceleration for gait and crime scene analysis

Sun, Yan, Hare, Jonathon and Nixon, Mark (2016) Detecting acceleration for gait and crime scene analysis At International Conference on Imaging for Crime Detection and Prevention, Spain. 23 - 25 Nov 2016. 6 pp.

Record type: Conference or Workshop Item (Other)

Abstract

Identifying criminals from CCTV footage is often a difficult task for crime investigations. The quality of CCTV is often low and criminals can cover their face and wear gloves (to withhold fingerprints) when committing a crime. Gait is the optimal choice in this circumstance since people can be recognised by their walking style, even at a distance with low resolution imagery. The location of the frame when the heel strikes the floor is essential for some gait analyses. We propose a new method to detect heel strikes: by radial acceleration which can also generalise to crime analysis. The frame and position of the heel strikes can be estimated by the quantity and the circle centres of radial acceleration, derived from the optical flow (using DeepFlow). Experimental results show high detection rate on two different gait databases and good robustness under different kinds of noise. We analysedetection of heel strikes to show robustness then we analyse crime scenes to show generalisation capability since violent crime often involves much acceleration. As such, we provide a new basis to a baseline technique in crime scene analysis.

PDF Detecting Acceleration for Gait and Crime Scene Analysis_YSun_JSHare_MSNixon.pdf - Accepted Manuscript
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More information

Accepted/In Press date: 3 October 2016
e-pub ahead of print date: November 2016
Venue - Dates: International Conference on Imaging for Crime Detection and Prevention, Spain, 2016-11-23 - 2016-11-25
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 402413
URI: http://eprints.soton.ac.uk/id/eprint/402413
PURE UUID: 669c9ba5-ec3d-4732-af66-0de6ec69fb82
ORCID for Jonathon Hare: ORCID iD orcid.org/0000-0003-2921-4283

Catalogue record

Date deposited: 07 Nov 2016 11:49
Last modified: 17 Jul 2017 17:51

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Contributors

Author: Yan Sun
Author: Jonathon Hare ORCID iD
Author: Mark Nixon

University divisions

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